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DOE OSTI2014

Theoretical limit of spatial resolution in diffuse optical tomography using a perturbation model

We have assessed the limit of spatial resolution of timedomain diffuse optical tomography (DOT) based on a perturbation reconstruction model. From the viewpoint of the structure reconstruction accuracy, three different approaches to solving the inverse DOT problem are compared. The first approach involves reconstruction of diffuse tomograms from straight lines, the second – from average curvilinear trajectories of photons and the third – from total banana-shaped distributions of photon trajectories. In order to obtain estimates of resolution, we have derived analytical expressions for the point spread function and modulation transfer function, as well as have performed a numerical experiment on reconstruction of rectangular scattering objects with circular absorbing inhomogeneities. It is shown that in passing from reconstruction from straight lines to reconstruction using distributions of photon trajectories we can improve resolution by almost an order of magnitude and exceed the accuracy of reconstruction of multi-step algorithms used in DOT. (optical tomography)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Tunable Lattice Reconstruction, Triangular Network of Chiral One-Dimensional States, and Bandwidth of Flat Bands in Magic Angle Twisted Bilayer Graphene

The interplay between interlayer van der Waals interaction and intralayer lattice distortion can lead to structural reconstruction in slightly twisted bilayer graphene (TBG) with the twist angle being smaller than a characteristic angle θ c . Experimentally, the θ c is demonstrated to be very close to the magic angle (θ≈1.08°). Here we address the transition between reconstructed and unreconstructed structures of the TBG across the magic angle by using scanning tunneling microscopy (STM). Our experiment demonstrates that both structures are stable in the TBG around the magic angle. By using a STM tip, we show that the two structures can be changed to each other and a triangular network of chiral one-dimensional states hosted by domain boundaries can be switched on and off. Consequently, the bandwidth of the flat band, which plays a vital role in the emergent strongly correlated states in the magic angle TBG, is tuned. This provides an extra control knob to manipulate the exotic electronic states of the TBG near the magic angle.

1-dimensional systems↗

DOE OSTI2021

DNCON2_Inter: predicting interchain contacts for homodimeric and homomultimeric protein complexes using multiple sequence alignments of monomers and deep learning

Deep learning methods that achieved great success in predicting intrachain residue-residue contacts have been applied to predict interchain contacts between proteins. However, these methods require multiple sequence alignments (MSAs) of a pair of interacting proteins (dimers) as input, which are often difficult to obtain because there are not many known protein complexes available to generate MSAs of sufficient depth for a pair of proteins. In recognizing that multiple sequence alignments of a monomer that forms homomultimers contain the co-evolutionary signals of both intrachain and interchain residue pairs in contact, we applied DNCON2 (a deep learning-based protein intrachain residue-residue contact predictor) to predict both intrachain and interchain contacts for homomultimers using multiple sequence alignment (MSA) and other co-evolutionary features of a single monomer followed by discrimination of interchain and intrachain contacts according to the tertiary structure of the monomer. We name this tool DNCON2_Inter. Allowing true-positive predictions within two residue shifts, the best average precision was obtained for the Top-L/10 predictions of 22.9% for homodimers and 17.0% for higher-order homomultimers. In some instances, especially where interchain contact densities are high, DNCON2_Inter predicted interchain contacts with 100% precision. We also developed Con_Complex, a complex structure reconstruction tool that uses predicted contacts to produce the structure of the complex. Using Con_Complex, we show that the predicted contacts can be used to accurately construct the structure of some complexes. Our experiment demonstrates that monomeric multiple sequence alignments can be used with deep learning to predict interchain contacts of homomeric proteins.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

StructureDistiller: Structural relevance scoring identifies the most informative entries of a contact map

Protein folding and structure prediction are two sides of the same coin. Contact maps and the related techniques of constraint-based structure reconstruction can be considered as unifying aspects of both processes. We present the Structural Relevance (SR) score which quantifies the information content of individual contacts and residues in the context of the whole native structure. The physical process of protein folding is commonly characterized with spatial and temporal resolution: some residues are Early Folding while others are Highly Stable with respect to unfolding events. We employ the proposed SR score to demonstrate that folding initiation and structure stabilization are subprocesses realized by distinct sets of residues. The example of cytochrome c is used to demonstrate how StructureDistiller identifies the most important contacts needed for correct protein folding. This shows that entries of a contact map are not equally relevant for structural integrity. The proposed StructureDistiller algorithm identifies contacts with the highest information content; these entries convey unique constraints not captured by other contacts. Identification of the most informative contacts effectively doubles resilience toward contacts which are not observed in the native contact map. Furthermore, this knowledge increases reconstruction fidelity on sparse contact maps significantly by 0.4 Å.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

MO-FG-CAMPUS-IeP2-04: Multiple Penalties with Different Orders for Structure Adaptive CBCT Reconstruction

Purpose: To combine total variation (TV) and Hessian penalty in a structure adaptive way for cone-beam CT (CBCT) reconstruction. Methods: TV is a widely used first order penalty with good ability in suppressing noise and preserving edges but leads to the staircase effect in regions with smooth intensity transition. The second order Hessian penalty can effectively suppress the staircase effect with extra cost of blurring object edges. To take the best of both penalties we proposed a novel method to combine both for CBCT reconstruction in a structure adaptive way. The proposed method adaptively determined the weight of each penalty according to the geometry of local regions. An specially-designed exponent term with image gradient involved was used to characterize the local geometry such that the weights for Hessian and TV were 1 and 0 respectively at uniform local regions and 0 and 1 at edge regions. For other local regions the weights varied from 0 to 1. The objective functional was minimized using the majorzationminimization approach. We evaluated the proposed method on a modified 3D shepp-logan and a CatPhan 600 phantom. The full-width-at-halfmaximum (FWHM) and contrast-to-noise (CNR) were calculated. Results: For 3D shepp-logan the reconstructed images using TV had an obvious staircase effect while those using the proposed method and Hessian preserved the smooth transition regions well. FWHMs of the proposed method TV and Hessian penalty were 1.75 1.61 and 3.16 respectively, indicating that both TV and the proposed method is able to preserve edges. For CatPhan 600 CNR values of the proposed method were similar to those of TV and Hessian. Conclusion: The proposed method retains favorable properties of TV like preserving edges and also has the ability in better preserving gradual transition structure as Hessian does. All methods performs similarly in suppressing noise. This work was supported in part by National Natural Science Foundation of China (NNSFC) under Grant Nos.60971112 and 61375018 grants from the Cancer Prevention and Research Institute of Texas (RP130109 and RP110562-P2) National Institute of Biomedical Imaging and Bioengineering (R01 EB020366) and a grant from the American Cancer Society (RSG-13-326-01-CCE).

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Examination of nucleon distribution with Bayesian imaging for isobar collisions

Relativistic collision of isobaric systems is found to be valuable in differentiating the nucleon distributions for nuclei with the same mass number. In recent contrast experiment of $^{96}_{44}$Ru + $^{96}_{44}$Ru versus $^{96}_{40}$Zr + $^{96}_{40}$Zr collisions at $\sqrt{s_{NN}}$ = 200 GeV, the ratios of multiplicity distribution, elliptic flow, triangular flow, and radial flow are precisely measured and found to be significantly different from unity, indicating the difference in the shapes of the isobar pair. Here, in this work, we investigate the feasibility of nuclear structure reconstruction from heavy-ion collision observables. We perform Bayesian Inference with employing the Monte-Carlo Glauber model as an estimator of the mapping from nuclear structure to the final state observables and to provide the mock data for reconstruction. By varying combination of observables included in the mock data, we find it plausible to infer Woods–Saxon parameters from the observables. We also observe that single-system multiplicity distribution for the isobar system, rather than their ratio, is crucial to simultaneously determine the nuclear structure for the isobar system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Transferable dispersion-aware machine learning interatomic potentials for multilayer transition metal dichalcogenide heterostructures

Stacking atomically thin transition metal dichalcogenides (TMDs) into heterostructures enables exploration of exotic quantum phases, particularly through twist-angle-controlled moiré superlattices. These structures exhibit novel electronic and optical behaviors driven by atomic-scale structural reconstruction. However, studying such systems with DFT is computationally demanding due to their large unit cells and van der Waals (vdW) interactions between layers. To address this, we develop a transferable neural network potential (NNP) that includes long-range vdW corrections up to 12Å with minimal overhead. Trained on vdW-corrected DFT data for Mo- and W-based TMDs with S, Se, and Te, the NNP accurately models monolayers, bilayers, heterostructures, and their interaction with h-BN substrates. It reproduces equilibrium structures, energy landscapes, phonon dispersions, and matches experimental atomic reconstructions in twisted WS2 and MoS2/WSe2 systems. We demonstrate that our NNP achieves DFT-level accuracy and high computational efficiency, enabling large-scale simulations of TMD-based moiré superlattices both with and without substrates.

materials for energy and catalysis↗

DOE OSTI2022

Strong Structural and Electronic Coupling in Metavalent PbS Moiré Superlattices

Moiré superlattices are twisted bilayer materials in which the tunable interlayer quantum confinement offers access to new physics and novel device functionalities. Previously, moiré superlattices were built exclusively using materials with weak van der Waals interactions, and synthesizing moiré superlattices with strong interlayer chemical bonding was considered to be impractical. Here, in this study, using lead sulfide (PbS) as an example, we report a strategy for synthesizing moiré superlattices coupled by strong chemical bonding. We use water-soluble ligands as a removable template to obtain free-standing ultrathin PbS nanosheets and assemble them into direct-contact bilayers with various twist angles. Atomic-resolution imaging shows the moiré periodic structural reconstruction at the superlattice interface due to the strong metavalent coupling. Electron energy loss spectroscopy and theoretical calculations collectively reveal the twist-angle-dependent electronic structure, especially the emergent separation of flat bands at small twist angles. The localized states of flat bands are similar to well-arranged quantum dots, promising an application in devices. This study opens a new door to the exploration of deep energy modulations within moiré superlattices alternative to van der Waals twistronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

SU-E-J-93: Development of Pre-Contoured Human Model Library in DICOM-RT Format for the Epidemiological Study of the Radiotherapy Patients

Purpose: Prior to 3D conformal radiation therapy planning, patient anatomy information was mostly limited to 2D beams-eye-view from the conventional simulator. To analyze the outcomes of such treatments for radiation late effects, 3D computational human models are often used in commercial treatment planning systems (TPSs). However, several underlying difficulties such as time-consuming manual delineation procedures of a large number of structures in the model have always limited its applications. Primary objective of this work was to develop a human model library for the epidemiological study by converting 3D-surface model organs to DICOM-RT format (DICOM-RT structure) using an in-house built software. We converted the ICRP reference human models to DICOM-RT models, which can be readily adopted for various dose calculations. Methods: MATLAB based code were utilized to convert the contour drawings extracted in text-format from the 3D graphic-tool, Rhinoceros into DICOM-RT structure format for 50 different organs of each model using a 16GB dual-core processor. The conversion periods were measured for each DICOM-RT models, and the reconstructed structure volumes were validated against the original 3D-surface models in the TPS. Ten reference hybrid whole-body models (8-pediatric and 2-adults) were automatically processed to create DICOM-RT computational human model library. Results: Mean contour conversion period was found to be 580 (N=2) and 394.5 (N=8) seconds for 50 organs in the adult and pediatric models respectively. A good agreement for large organs (NRMSD <1.0%) and small organs (NRMSD <7.7%) was also observed between the original volumes and corresponding DICOM-RT structure volumes of the organs. Conclusion: The ICRP reference human models were converted into DICOM-RT format to support the epidemiological study using a large cohort of conventional radiotherapy patients. Due to its DICOM-compatibility, the library may be implemented to many other different applications. We also expect to develop the library by including additional models in future.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

OH PLIF Visualization of an Optically Accessible Rotating Detonation Combustor

OH PLIF imaging has been successfully conducted within an optically accessible race- track shaped rotating detonation combustor. The OH PLIF images taken in this study corroborate the overall flow field structure reconstructed from previous OH* chemilumi- nescence studies conducted on the same combustor. However, the increased spatial and temporal resolution achieved with the OH PLIF technique allowed for the identification of previously unknown structures present in the detonation wave and its wake. These struc- tures appear as non-uniformities in the OH PLIF signal throughout the channel. Smaller scale structures range from variations in light intensity all the way to seemingly unburnt gas pockets passing through the detonation wave, suggesting non uniform reaction across the propagating detonation wave. Also present in the flow is a relatively large structure, consisting of a dark band surrounded by regions of higher OH intensity that trails the detonation wave. This band is hypothesized to be a result of the effect of secondary waves on the injection system and subsequent fill region composition stratification. Both of these flow structures represent potential avenues for performance loss through off-design mixing and heat release being uncoupled from the detonation wave.

Chacon, Fabian↗

DOE OSTI2014

Modeling and characterizing anisotropic inclusion orientation in heterogeneous material via directional cluster functions and stochastic microstructure reconstruction

We present a framework to model and characterize the microstructure of heterogeneous materials with anisotropic inclusions of secondary phases based on the directional correlation functions of the inclusions. Specifically, we have devised an efficient method to incorporate both directional two-point correlation functions S{sub 2} and directional two-point cluster functions C{sub 2} that contain non-trivial topological connectedness information into the simulated annealing microstructure reconstruction procedure. Our framework is applied to model an anisotropic aluminum alloy and the accuracy of the reconstructed structural models is assessed by quantitative comparison with the actual microstructure obtained via x-ray tomography. We show that incorporation of directional clustering information via C{sub 2} significantly improves the accuracy of the reconstruction. In addition, a set of analytical “basis” correlation functions are introduced to approximate the actual S{sub 2} and C{sub 2} of the material. With the proper choice of basis functions, the anisotropic microstructure can be represented by a handful of parameters including the effective linear sizes of the iron-rich and silicon-rich inclusions along three orthogonal directions. This provides a general and efficient means for heterogeneous material modeling that enables one to significantly reduce the data set required to characterize the anisotropic microstructure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Enhanced optoelectronic and elastic responses in fluorinated penta-BCN

We report surface passivation in two-dimensional (2D) materials is one of the best approaches to modulate the structural, dynamical, and mechanical stabilities thereby enhancing chemical and physical properties for optoelectronic applications. Here, we report an ab-initio investigation on structurally, thermally, dynamically, and mechanically stable, and experimentally feasible fluorinated penta-BCN (F-BCN) monolayer. The structural reconstruction after fluorination, increases bond lengths and thickness to reduce the average stiffness and elasticity attaining the mechanical isotropy. Nevertheless, the value of 2D Young’s modulus of F-BCN is comparable to the pristine structure at 6% of compression without mechanical instability. A significant bandgap tailoring is achieved, similar to that of mechanical sensitivity, due to applied strain. Remarkably, following the fluorine passivation, the monolayer’s induced wide direct bandgap semiconducting behavior improves optical absorbance and reflectivity, decreases energy loss, changes optical anisotropy, and makes it a promising candidate material for optoelectronic and nanomechanical applications.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Representative volume element model of lithium-ion battery electrodes based on X-ray nano-tomography

For this, a new model that keeps all major advantages of the single-particle model of lithium-ion batteries (LIBs) and includes three-dimensional structure of the electrode was developed. Unlike the single spherical particle, this model considers a small volume element of an electrode, called the Representative Volume Element (RVE), which represent the real electrode structure. The advantages of using RVE as the model geometry was demonstrated for a typical LIB electrode consisting of nano-particle LiFePO 4 (LFP) active material. The three-dimensional morphology of the LFP electrode was reconstructed using a synchrotron X-ray nano-computed tomography at the Advanced Photon Source of the Argonne National. A 27 μm 3 cube from reconstructed structure was chosen as the RVE for the simulation purposes. The model was employed to predict the voltage curve in a half-cell during galvanostatic operations and validated with experimental data. The simulation results showed that the distribution of lithium inside the electrode microstructure is very different from the results obtained based on the single-particle model. The range of lithium concentration is found to be much greater, successfully illustrates the effect of microstructure heterogeneity.

25 ENERGY STORAGE↗

DOE OSTI2015

Helium: lifting high-performance stencil kernels from stripped x86 binaries to halide DSL code

Highly optimized programs are prone to bit rot, where performance quickly becomes suboptimal in the face of new hardware and compiler techniques. In this paper we show how to automatically lift performance-critical stencil kernels from a stripped x86 binary and generate the corresponding code in the high-level domain-specific language Halide. Using Halide's state-of-the-art optimizations targeting current hardware, we show that new optimized versions of these kernels can replace the originals to rejuvenate the application for newer hardware. The original optimized code for kernels in stripped binaries is nearly impossible to analyze statically. Instead, we rely on dynamic traces to regenerate the kernels. We perform buffer structure reconstruction to identify input, intermediate and output buffer shapes. Here, we abstract from a forest of concrete dependency trees which contain absolute memory addresses to symbolic trees suitable for high-level code generation. This is done by canonicalizing trees, clustering them based on structure, inferring higher-dimensional buffer accesses and finally by solving a set of linear equations based on buffer accesses to lift them up to simple, high-level expressions. Helium can handle highly optimized, complex stencil kernels with input-dependent conditionals. We lift seven kernels from Adobe Photoshop giving a 75 % performance improvement, four kernels from Irfan View, leading to 4.97 x performance, and one stencil from the mini GMG multigrid benchmark netting a 4.25 x improvement in performance. We manually rejuvenated Photoshop by replacing eleven of Photoshop's filters with our lifted implementations, giving 1.12 x speedup without affecting the user experience.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Electronic reconstruction at the polar (111)-oriented oxide interface

Atomically flat (111) interfaces between insulating perovskite oxides provide a landscape for new electronic phenomena. For example, the graphene-like coordination between interfacial metallic ion layer pairs can lead to topologically protected states [Xiao et al., Nat. Commun. 2, 596 (2011) and A. Rüegg and G. A. Fiete, Phys. Rev. B 84, 201103 (2011)]. The metallic ion/metal oxide bilayers that comprise the unit cell of the perovskite (111) heterostructures require the interface to be polar, generating an intrinsic polar discontinuity [Chakhalian et al., Nat. Mater. 11, 92 (2012)]. Here, we investigate epitaxial heterostructures of (111)-oriented LaAlO 3 /SrTiO 3 (LAO/STO). We find that during heterostructure growth, the LAO overlayer eliminates the structural reconstruction of the STO (111) surface with an electronic reconstruction, which determines the properties of the resulting two-dimensional conducting gas. This is confirmed by transport measurements, direct determination of the structure and atomic charge from coherent Bragg rod analysis, and theoretical calculations of electronic and structural characteristics. Interfacial behaviors of the kind discussed here may lead to new growth control parameters useful for electronic devices.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Grazing-Angle Neutron Diffraction Study of the Water Distribution in Membrane Hemifusion: From the Lamellar to Rhombohedral Phase

The water distribution between lipid bilayers is important in understanding the role of the hydration force at different steps of the membrane fusion pathway. Here in this study, we used grazing-angle neutron diffraction to map out the water distribution in lipid bilayers transiting from a lamellar structure to the hemifusion “stalk” structure in a rhombohedral phase. Under osmotic pressure exerted by different levels of relative humidity, the lipid membrane sample was maintained in equilibrium at different lattices suitable for neutron diffraction. The D 2 O used to hydrate the lipid membrane sample stood out from the lipid in the reconstructed structure because of its much higher coherent neutron scattering length density. The density map indicates that water dissociated from the headgroup in the lamellar phase. In the rhombohedral phase, water was significantly reduced and was squeezed into pockets around the stalk. This study complements earlier structural studies by grazing-angle X-ray diffraction, which is sensitive to only the parts of the structure with high electron density (such as phosphors). The experiment also demonstrated that the recently developed time-of-flight small-angle neutron scattering beamline at the Spallation Neutron Source is suitable for grazing-angle neutron diffraction to provide the structures of large unit cells on the order of a few nanometers, such as biomembrane structures.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Electrical anisotropy and coexistence of structural transitions and superconductivity in IrT e 2

In this work, we report experimental investigations of the electrical transport, magnetic, and thermodynamic properties of IrTe 2 single crystals. The resistivity, magnetization, and specific heat display anomalies at T S1 ≈ 283K,T S2 ≈ 167K, and T c ≈2.5K, corresponding to two structural and one superconducting phase transitions, respectively, demonstrating the coexistence of all of these transitions in high-quality stoichiometric samples. While there is little magnetic anisotropy, a large ab-plane (ρab) and c-axis (ρc) electrical resistivity ratio (ρ c /ρ ab ≈730 at T=4K) is observed. This two-dimensional (2D) electronic character is further reflected in the disparate temperature dependences of ρ ab and ρ c , with ρab exhibiting a Fermi-liquid-like T 2 dependence below ~25K, while ρc deviates significantly from this standard metallic behavior. In contrast, the magnetization is almost isotropic and negative over a wide temperature range. Furthermore, this can be explained by larger diamagnetism induced by electronic structure reconstruction as probed by the Hall effect and smaller positive contribution from itinerant electrons due to a low density of states (DOS) at the Fermi level. A small electronic specific heat coefficient with γ ≈ 1.8mJ/molK 2 confirms this assertion. This implies that IrTe 2 is a weakly coupled superconductor. The connection between the superconductivity and the two structural transitions is discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Determination of crystallographic intensities from sparse data

X-ray serial microcrystallography involves the collection and merging of frames of diffraction data from randomly oriented protein microcrystals. The number of diffracted X-rays in each frame is limited by radiation damage, and this number decreases with crystal size. The data in the frame are said to be sparse if too few X-rays are collected to determine the orientation of the microcrystal. It is commonly assumed that sparse crystal diffraction frames cannot be merged, thereby setting a lower limit to the size of microcrystals that may be merged with a given source fluence. The EMC algorithm [Loh & Elser (2009), Phys. Rev. E , 80 , 026705] has previously been applied to reconstruct structures from sparse noncrystalline data of objects with unknown orientations [Philipp et al. (2012), Opt. Express , 20 , 13129–13137; Ayyer et al. (2014), Opt. Express , 22 , 2403–2413]. Here, it is shown that sparse data which cannot be oriented on a per-frame basis can be used effectively as crystallographic data. As a proof-of-principle, reconstruction of the three-dimensional diffraction intensity using sparse data frames from a 1.35 kDa molecule crystal is demonstrated. The results suggest that serial microcrystallography is, in principle, not limited by the fluence of the X-ray source, and collection of complete data sets should be feasible at, for instance, storage-ring X-ray sources.

Chemistry↗